knitr::include_graphics('QGIS_MAP.png')
QGIS Map

QGIS Map

Assignment 1 – Critical Evaluation

The generated choropleth maps demonstrate two different software processes to create a visualization of the same basic quantitative data from the Global Information System on Alcohol and Health (GISAH). For this comparative analysis QGIS was chosen as the GUI system and RStudio as the code-based system. Both types of software have very different workflows and characteristics that lead to various benefits and drawbacks between the two. Overall the GUI system is much more user-friendly for beginners and fairly intuitive after quickly playing around with the features (Computer 2018). Since most tools and commands are already built into the program, once you know what they can do the process of getting through the steps of creating a map becomes very quick. In my case, after the datasets I chose had been combined with shapefiles to create a map, it was fast and easy to alter the cartographic features towards my final product. This form of direct manipulation is what GUI systems do well and it makes practicing good cartographic skills straightforward for inexperienced users (Soft 2018).

Command line interface usability is not as intuitive for a user that has little to no experience with scripting, which was the case I found myself in when trying to create my own map. The workflow within RStudio assumes that the user is familiar with standard code composition, which is the biggest drawback for beginners. If users are not aware of the proper syntax and tools necessary to create their desired product, this process is more time consuming to get to a finished product (Computer 2018). I also found it to be quite slow when making simple tweaks to the standard map features in R, since you have to re-send the whole code each time you make one small adjustment and wait for the map to reload. In terms of the ease of switching between different types of maps such as interactive, static, or multiples just to name a few, once you have your files created, libraries downloaded and basic commands written it is very quick. This sort of system is also much better suited to larger amounts of data and repetitive, complex tasks that can be sorted with just a few bits of code (Soft 2018).

In my own experience, I found my map in QGIS to manifest much quicker than in R, for the simple reason that I have slightly more experience with GUI systems. However, once I had created a static map in RStudio I was able to easily transform that into an interactive version and in my opinion this was a more interesting way of displaying my findings, even though I felt I was able to more easily personalize my map in QGIS. As far as cartographic practice goes, I felt that my QGIS map ticked all the boxes for what a “good” maps needs, such as orientation, scale and an intuitive color palettes. I found that it was simple to get those basics in R, but harder to be creative with colors and fonts, even though I preferred the interactive form of data presentation more. In the context of creating a simple choropleth map, for my experience level it was cleaner to do so in QGIS, or on GUI-based systems. However, the ability to do more with the same basic data and shapefile by changing only a few lines of code in is a much more intriguing way of representing one’s findings and possibly more efficient when larger groups of data are involved.

Sources:

Computerhope.com. (2018). Command line vs. GUI. [online] Available at: https://www.computerhope.com/issues/ch000619.htm [Accessed 30 Oct. 2018].

Softpanorama.org. (2018). GUI vs Command line interface. [online] Available at: http://www.softpanorama.org/OFM/gui_vs_command_line.shtml#Advantages_and_disadvantages_of_GUI_vs_command_line [Accessed 30 Oct. 2018].

http://apps.who.int/gho/data/node.gisah.A1039?lang=en&showonly=GISAH

https://github.com/juliapartheymueller/map_europe/blob/master/code/map_europe.r https://ourworldindata.org/alcohol-consumption#data-sources shapefile from EUROSTAT